Compressed Sensing is a signal processing technique that reconstructs a signal from fewer samples than traditionally required, leveraging the sparsity of the signal in some domain. It exploits the idea that many natural signals are sparse or compressible in a transform domain, allowing for efficient acquisition and reconstruction using optimization algorithms.