Choosing the right distance metric and linkage method depends on the nature of the data and the specific problem you are trying to solve. Some common distance metrics include Euclidean distance, Manhattan distance, and cosine similarity. Linkage methods, such as single linkage, complete linkage, average linkage, and Ward's method, determine how the distance between clusters is calculated. It is essential to experiment with different combinations of distance metrics and linkage methods to find the best fit for your data and problem.