#P-Completeness of the Hosoya Index The description from Wikipedia mentions that it is #P-Complete to compute, but there are methods.  What is a layman's explanation to this?
A matching $M$ is called perfect for a graph $G$ when all vertices of a graph are matched in $M$.

Computing the number of perfect matchings is a well-known #P-complete problem and shown to be equivalent to computing the permanent of the biadjacency matrix of the graph. Now note that each perfect matching, by removing edges produces $2^{n}-1$ different matchings (consider each subset of edges, which is a smaller matching, we do not consider the empty set). Also, each perfect matching prohibits exactly $\binom{n}{k}$ matchings of size $k$ from being maximal but non-perfect, since they are subsets of this perfect matching. Given those kinds of restrictions, one can certainly upper bound the number of perfect matchings given the number of matchings and perhaps it is also to use additional information to do a precise calculation.

Perhaps you should take a look at the paper "Two-dimensional monomer-dimer systems are computationally intractable" (reference 5 in the wikipedia article). It seems to rely on the fact that counting matchings (all of them, see the comments) remains #P-complete for planar graphs. Interestingly enough, counting perfect matchings for planar graphs in in $P$, i.e. can be computed in polynomial time (in a deterministic way).