Algorithms to correct misspelled word?
Standard OCR software already incorporates this idea: it has a corpus of words, along with their frequency of occurrence, and uses this to correct  errors.

How does it work?  OCR doesn't just output a letter at each position; it actually produces a probability distribution on letters.  For example, its output might be something like: I'm 99% sure the first letter is a 'h'; I'm 60% sure the second letter is a 'u', but there's is a 20% chance it is a 'o', and a 15% chance it is an 'a', and so on.  This lets you consider many possibilities for what the word might be, and combine the probabilities from the OCR with the frequency of occurrence of that possibility in English text to come up with an educated guess about what the actual word is.

For instance, if the OCR says "5% chance this is 'hurze", 2% chance this is 'horse'", and you know that 'horse' occurs 100x more often than 'hurze' in English language, you should guess that the corresponding word is probably 'horse', not 'hurze'.

As Yuval Filmus says, another approach is to look for a dictionary word that is within edit distance 1 or 2 of the raw output from the OCR.

If your OCR software is any good, it might already be doing this sort of correction.  Sometimes you can give the OCR software a custom dictionary of words that tend to appear in your documents, to help it do this sort of correction.