Heuristic algorithms are problem-solving methods that use practical approaches to find satisfactory solutions quickly, rather than optimal ones. They are particularly useful for complex problems where traditional methods may be too slow or difficult to apply. By employing rules of thumb, educated guesses, or trial-and-error, heuristic algorithms can efficiently navigate large search spaces. These algorithms are commonly used in fields like artificial intelligence, operations research, and computer science. Examples include genetic algorithms, which mimic natural selection, and A* search algorithm, which finds the shortest path in graphs. Heuristic methods help tackle real-world problems effectively, even when perfect solutions are unattainable.