So, our initial hypothesis certainly plays an important role in the case of statistical learning models.
But, in the case of machine learning(ML) models, we directly run the ML algorithms on the model,
thus allowing the data to speak out instead of directing it in a certain direction with our initial hypothesis/assumptions.