The four primary Machine Learning models are Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning. Supervised Learning models learn from labeled data to predict outcomes for unseen data. Unsupervised Learning models identify patterns in unlabeled data, commonly used for clustering or anomaly detection. Semi-Supervised Learning operates with a mix of labeled and unlabeled data, making it a middle ground between supervised and unsupervised learning. Reinforcement Learning models learn to make decisions by interacting with an environment, aiming to maximize cumulative reward.