Machine Learning is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to perform tasks without explicit programming. Instead of being manually programmed with specific instructions to carry out a task, machine learning systems use data to learn patterns and make decisions or predictions based on that data.

The process involves training a model on a dataset, where the model learns to identify trends and relationships within the data. Once trained, the model can be used to make predictions or classifications on new, unseen data. Machine learning techniques can be categorized into three main types: supervised learning, where the model is trained on labeled data; unsupervised learning, where it identifies patterns in unlabeled data; and reinforcement learning, where the model learns to make decisions by receiving rewards or penalties based on its actions.

Applications of machine learning can be found in various fields, including finance (for fraud detection), healthcare (for disease diagnosis), marketing (for customer segmentation), and many others, making it a vital tool in contemporary data analysis and automation.