The λ-biased random walk on a binary tree of depth n is the continuous-time Markov chain that has unit mean holding times and, when at a vertex other than the root or a leaf of the tree in question, has a probability of jumping to the parent vertex that is λ times the probability of jumping to a particular child. (From the root, it chooses one of the two children with equal probability.) For this process, when λ<1, we derive an n→∞ scaling limit for the cover time, that is, the time taken to visit every vertex. The distributional limit is described in terms of a jump process on a Cantor set that can be seen as the asymptotic boundary of the tree. This conclusion complements previous results obtained when λ≥1.