The three stages to build hypotheses or a model in machine learning are:

A) Data preprocessing, feature selection, and model training.
B) Data collection, data preprocessing, and model evaluation.
C) Model selection, hyperparameter tuning, and evaluation.
D) Feature engineering, model training, and model evaluation.