Supervised learning: Which type of machine learning does this describe?

Learning to predict known labels from labeled training examples is supervised learning.

The question

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1. Supervised learning, where a model learns a mapping from inputs to known, labeled target outputs. ✓

   Correct: learning from labeled examples to predict outcomes for new inputs is the definition of supervised learning.
2. Unsupervised learning, where a model finds structure or clusters in data lacking target labels.

   Plausible but wrong: unsupervised learning works on unlabeled data, whereas here labels are present.
3. Reinforcement learning, where an agent learns a policy through rewards from interacting with settings.

   Plausible but wrong: reinforcement learning is driven by reward signals from actions, not fixed labeled examples.
4. Transfer learning, where a model reuses knowledge from one task to accelerate a related second task.

   Plausible but wrong: transfer learning describes reusing prior knowledge, not the labeled-data paradigm itself.

How to remember it

Learning to predict known labels from labeled training examples is supervised learning.

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