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 relying on rule-based decision-making, machine learning systems "learn" from data, improving their performance as they are exposed to more information. This technology is used in various applications, from recommendation engines that personalize your online shopping experience to autonomous vehicles that navigate roads without human intervention. Machine learning can be categorized into different types, including supervised learning, where the model is trained on labeled data, and unsupervised learning, where the model uncovers patterns in unlabeled data. The field has seen significant advancements in recent years, driven by the availability of large datasets and computational power, but it also presents challenges such as data privacy, ethical considerations, and the risk of perpetuating existing biases present in the training data.