Why is min-max scaling or standardization often applied before training algorithms like k-NN or SVM?

A Because these algorithms cannot process negative numbers B Because these algorithms rely on distance or dot-product calculations, and features on larger numeric scales would otherwise dominate the result regardless of their actual importance C Because scaling guarantees the model will not overfit D Because unscaled data cannot be split into train and test sets