Logarithmic time refers to a type of algorithmic efficiency where the time it takes to complete a task increases slowly as the size of the input grows. This means that even if the input size doubles, the time taken only increases by a small amount. An example of this is the binary search algorithm, which quickly finds an item in a sorted list by repeatedly dividing the list in half. In contrast to linear time, where time increases directly with input size, logarithmic time is much more efficient for large datasets. This efficiency is crucial in computer science, especially when dealing with large amounts of data, as it allows for faster processing and quicker results.