Neuromorphic Computing is a type of computing that mimics the way the human brain processes information. It uses specialized hardware designed to replicate neural networks, allowing for more efficient data processing and learning. This approach can lead to faster and more energy-efficient computations compared to traditional computing methods. By imitating the brain's structure and function, neuromorphic systems can perform tasks like pattern recognition and sensory processing more effectively. Researchers are exploring its applications in areas such as artificial intelligence, robotics, and machine learning, aiming to create smarter and more adaptive technologies.