Neural networks mimic the human brain's structure and functionality by using interconnected nodes (neurons) to process data. These artificial networks consist of layers, including an input layer, one or more hidden layers, and an output layer. Each connection between neurons has an associated weight that adjusts based on learning algorithms during training. Neural networks excel at recognizing patterns and making predictions by simulating brain-like processing, thus enabling diverse applications, from image recognition to natural language processing.