Machine learning relies on algorithms and statistical models to make predictions or decisions based on input data. This technology processes large datasets to identify patterns and trends, which are then used to train models that can infer outcomes for new data. Various techniques such as supervised learning, unsupervised learning, and reinforcement learning define how the model learns from data. By constantly refining its predictions based on feedback, machine learning is applicable across diverse fields like finance, healthcare, and marketing, driving innovation through data-driven insights.