Levenshtein distance is a measure of how different two strings are by counting the minimum number of single-character edits required to change one string into the other. These edits can include insertions, deletions, or substitutions of characters. For example, transforming the word "kitten" into "sitting" requires three edits: substituting 'k' with 's', 'e' with 'i', and adding 'g' at the end. This concept is widely used in various fields, including computer science, natural language processing, and spell checking. By calculating the Levenshtein distance, algorithms can determine how closely related two words or phrases are, aiding in tasks like autocorrect and data matching.