Machine learning is a type of artificial intelligence that allows systems to improve their performance on a specific task by learning from data, without being explicitly programmed. This is done by using algorithms that can process large amounts of data and recognize patterns within it, in order to make predictions or take actions based on that information.

One of the most common examples of machine learning is in the field of image recognition. This is when a system is trained to identify objects in images, such as cars, buildings, or animals. To do this, the system is fed a large dataset of labeled images, where each image has been manually labeled with the objects it contains. The machine learning algorithm then uses this data to learn the characteristics of each object and develop a model that can identify them in new images.

Another example of machine learning is in the field of natural language processing (NLP). This is when a system is trained to understand and generate human language, such as for chatbots or virtual assistants. To do this, the system is fed a large dataset of human language data, such as transcripts of conversations or written documents. The machine learning algorithm then uses this data to learn the structure and meaning of human language, and develop a model that can understand and generate it.

In both of these examples, the machine learning algorithm uses the labeled data to learn the characteristics of the task at hand, and then uses this knowledge to make predictions or take actions on new data. This allows the system to improve its performance over time, without the need for explicit programming.