The term “haplotype block” is commonly used in the developing field of haplotype-based inference methods. We argue that the term should be defined based on the structure of the Ancestral Recombination Graph (ARG), which contains complete information on the ancestry of a sample. We use simulated examples to demonstrate key features of the relation between haplotype blocks and ancestral structure, emphasising the stochasticity of the processes that generate them. Even the simplest cases of neutrality or of a “hard” selective sweep produce a rich structure, often missed by commonly used statistics. We highlight a number of novel methods for inferring haplotype structure, based on the full ARG, or on a sequence of trees, and illustrate how they can be used to define haplotype blocks using an empirical dataset. While the arrival of computationally efficient methods makes it possible to apply these concepts broadly, existing and new methods could include tools for the identification and explore haplotype blocks, as we define them. Understanding and applying the concept of the haplotype block will be essential to fully exploit long and linked-read sequencing technologies.