Tensor Cores are specialized processing units designed to accelerate deep learning and high-performance computing tasks by performing mixed-precision matrix multiply and accumulate operations in a single clock cycle. They significantly reduce the time required for training and inference in neural networks, enabling faster and more efficient computation of complex models.