Machine learning algorithms are computational methods that enable computers to identify patterns in data and make predictions or decisions without requiring explicit programming for every task. They learn from examples and improve their performance as they process relevant data. Common types include supervised learning, unsupervised learning, and reinforcement learning. Examples of widely used algorithms include linear regression, decision trees, k-means clustering, and neural networks. These methods support applications such as fraud detection, recommendation systems, image recognition, and demand forecasting. Businesses exploring AI technologies should select algorithms based on their objectives, data quality, and performance requirements to achieve useful and reliable results.