O, Theta, and Omega are independent from best, worst, and average case. You can mathematically establish upper, lower, or exact bounds on any of the average, best, or worst cases.
It is perfectly valid to say "the best case is O(n)" which means the best case scales no worse than linearly. The "no worse" here is not describing the best case, but rather the strictness of your bound. You could say a sort algorithm is O(n!) since, yes, it does scale no worse than n! but it's not particularly helpful information.
Big O notation is used imprecisely frequently (see also people saying a dataset is O(millions) to describe scale).
It is perfectly valid to say "the best case is O(n)" which means the best case scales no worse than linearly. The "no worse" here is not describing the best case, but rather the strictness of your bound. You could say a sort algorithm is O(n!) since, yes, it does scale no worse than n! but it's not particularly helpful information.
Big O notation is used imprecisely frequently (see also people saying a dataset is O(millions) to describe scale).