A retailer wants to group customers into natural segments based on purchase behavior — but there are no labeled categories to learn from. Which ML approach applies?
A.Supervised learning
Supervised learning needs labeled training data — none exists here.
B.Unsupervised learning
Correct. Clustering unlabeled data into segments is unsupervised learning.
C.Reinforcement learning
Reinforcement learning optimizes sequential decisions via rewards.
D.Transfer learning
Transfer learning adapts a pretrained model — not about unlabeled grouping.
Why this answer
Unsupervised learning finds structure in unlabeled data — clustering customers into segments is its canonical use case. Supervised learning requires labeled examples of the answer.
Correct answer: B · Last reviewed 2026-10-26
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