Global alignment is a method used in bioinformatics to compare two sequences, such as DNA, RNA, or proteins, across their entire length. This technique aims to identify the best possible alignment by matching similar characters and accounting for gaps, which helps in understanding evolutionary relationships and functional similarities. The process involves algorithms like Needleman-Wunsch that systematically evaluate all possible alignments to find the one with the highest score based on predefined criteria. Global alignment is particularly useful when the sequences being compared are of similar length and share a significant amount of similarity, providing insights into their biological significance.