A sparse matrix is a type of matrix in which most of the elements are zero. This characteristic makes sparse matrices efficient for storage and computation, as they can be represented using specialized data structures that only store the non-zero elements. This is particularly useful in fields like computer science, engineering, and data science, where large datasets often contain many zero values. Sparse matrices are commonly used in various applications, such as machine learning, graph theory, and scientific computing. By focusing on the non-zero elements, algorithms can run faster and consume less memory, making it easier to handle large-scale problems without unnecessary resource usage.