Speaking as an occasional reviewer for journals, when I read a paper proposing a new heuristic or metaheuristic my first question is "does it work?", which is independent of the programming language used. My second question is "does it work better than existing methods?", which can be interpreted in one of two ways: it gets better results than currently accepted methods in the same amount of time; or it gets comparable results faster. Depending on the underlying type of problem being solved, "accepted methods" might include running a commercial optimization solver in a heuristic way (set a time limit, tweak a few settings and see how good the incumbent solution is).
So this ties into the question @PeterD put in his comment. If this is a new, previously unsolved, problem and it does not fit into a category (LP, MILP, ...) for which solvers exist, just producing "reasonable" results in "reasonable" time is grounds for publication. If there are no commonly used heuristics for the problem, getting a solution that is fairly good in a reasonable time may be enough for publication, even if commercial solvers do better, because not everyone can afford commercial solvers. If, say, the problem is frequently solved (by practitioners and/or in the research literature) using the horny snail metaheuristic, than I would expect you as author to demonstrate that your metaheuristic is faster than horny snail, either by running both of them on the same examples using the same hardware or by citing published times for horny snail on publicly available test problems and then beating those times with your heuristic (on hardware comparable to what was used for the published times).
Now, can you accomplish any of that in Python. Quite possibly. The published times for other heuristics might have been generated using Python code, or code in languages "slower" than C/C++. There is also the question of coding skill: your "tight" Python code might run faster than someone else's sloppy C++ code. Also, libraries play a role. The bulk of the computing time spent by your heuristic might occur in a Python library, written in C/C++ by someone who worked to optimize their code.
If nothing else, you could start by coding in Python and see if your heuristic works (valid results, reasonably close to optimal in reasonable time and memory). If you think it has merit but is not yet publishable, maybe you could bring on a coauthor with C/C++ programming chops (or hire someone to recode it).