Neural Networks are a series of algorithms that attempt to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. They consist of interconnected layers of nodes (neurons), each performing simple computations. Neural networks learn to map input data to desired outputs by adjusting the weights of the connections based on the error of the predictions. They are the foundation of deep learning, enabling complex models such as Convolutional Neural Networks (CNNs) for image processing and Recurrent Neural Networks (RNNs) for sequential data. Neural networks are used in a wide range of applications, including image and speech recognition, natural language processing, and autonomous systems.