Supervised Learning - In supervised machine learning, a model makes predictions or decisions based on past or labeled data. Labeled data refers to sets of data that are given tags or labels, and thus made more meaningful.
Unsupervised Learning - In unsupervised learning, we don't have labeled data. A model can identify patterns, anomalies, and relationships in the input data.
Reinforcement Learning - Using reinforcement learning, the model can learn based on the rewards it received for its previous action