You are discussing common machine learning approaches and when to use them. You want to explain the distinction clearly in a way that connects the concepts to how models are trained and evaluated.
Explain the difference between supervised and unsupervised learning.
Understanding of labeled versus unlabeled learningAbility to connect concepts to real model choicesAwareness of feature engineering differencesHow evaluation changes across learning settings