Don't understand minimax algorithm in terms of chess I'm new to minimax algorithm, but i understand it's entire concepts as it's easy, my biggest issue is understanding it's implementation to my chess game, no internet solution answers this question

black or white players comprises of several pieces, so what piece is the AI predicting moves for, as the player could move any of their 16 pieces?

all i keep seeing is that we need to write the code to look several moves ahead in which the player could potentially make, my issue is that there are multiple pieces the player could pick from so what moves exactly are we talking about and how would the AI determine which of its pieces to move based on that. 

I just need a brief explanation, no source code or how to's. I've spent days trying to wrap my head around this concept.
In minimax you fully explore the game tree. So the answer to "which piece" is all of them. All possible moves for all movable pieces. And then it selects the minimum or maximum (depending on the depth) out of those options.

Obviously this isn't feasible which is why we never apply raw minimax to chess. It is always with other optimizations such as alpha-beta, and stopping after a certain depth and using a heuristic evaluation of that position instead of continuing.