Which of the following best describes supervised learning in machine learning?

Supervised learning involves training a model using labeled datasets where the algorithm learns to map inputs to the correct output labels. Once trained, the model can predict labels for new, unseen data. It is widely used for classification and regression problems in machine learning. Why Other Options are Wrong: b) Clustering data without labels is unsupervised learning, not supervised learning. c) Continuous learning from feedback describes reinforcement learning. d) Interaction with an environment also refers to reinforcement learning. e) Time series prediction is a specific application of supervised learning but does not define it comprehensively.