Parallel algorithms are computational methods that divide a problem into smaller subproblems, which can be solved simultaneously by multiple processors or cores. This approach enhances efficiency and reduces the time required to complete complex tasks, making it particularly useful in fields like computer science, data analysis, and machine learning. These algorithms leverage the capabilities of modern hardware, such as multi-core processors and distributed computing systems. By executing operations in parallel, they can handle large datasets and perform computations faster than traditional sequential algorithms, which process tasks one at a time.