As long as the meaning of alpha is the probability of a Type I error then any of your listed corrections can be applied to any of your tests. You might say that the corrections for Type II error are underlying test agnostic because they correct the alpha inflation, which would be constant across tests of different kinds.
In your case, where you've implied that you're starting with an ANOVA that shows there is something significant, then the correction can also depend on whether you had specific hypotheses about individual comparisons. I tend to like to just report the standard confidence intervals of the effects in question. I know this doesn't have any corrections for multiple comparisons and is subject to Type II error even with a significant ANOVA (it's equivalent to Fisher's PLSD) but I report it in such a way as to imply that future research should look "here" rather than saying my results are definitive on the matter.
It's hard to advise you on exactly what to do without seeing the pattern of results and also your idea of what should have happened (or whether it was entirely exploratory). Perhaps you want to craft a question that includes your analysis thus far, some of your hypotheses about what would happen, and maybe even a couple of reporting alternatives. Then you'll get some really good results on here. Better questions get better answers.
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