With the advent of the Rel. 16 of the 5G system (5GS), 3GPP introduced the feature of integrated access and backhaul (IAB), which enables multi-hop cellular communications for coverage extension at the radio access network (RAN). 3GPP and ETSI have also worked towards the tight integration of 5G-Advanced and Multi-access Edge Computing (MEC) infrastructures, targeting at seamless offloading of computation loads in the near area of user equipments (UEs). In this work, we present a benchmark analytical model that leverages the enhanced measurement capabilities of next-generation (NG)-RAN base stations (BSs) and the user equipments (UEs) towards locationinformed MEC host selection in IAB-enabled 6G systems. We focus on the scenario where the UE selects between two candidate MEC hosts by pulling knowledge from the Location Management Function (LMF) on the relative positions of IAB donor BSs. Using as a key metric the aggregate length of the end-to-end IAB path separating the UE and the candidate MEC hosts, we derive exact and approximate expressions on the IAB path length distribution and assess the performance of a simplified yet location-informed MEC host selection strategy in IAB-enabled NG-RAN setups.