Algorithm used in KNeighborsClassifier with sparse input?
No, it means that if the input is sparse, whichever value passed to the argument algorithm will be ignored and brute force algorithm will be used (which is equivalent to algorithm='brute')
For classification algorithm KNeighborsClassifier what does fitting on a sparse input mean?
Does it mean if I have x_train and x_test as sparse csr matrix and If I fit on x_train and don't specify algorithm it will automatically choose brute? can anyone clear this confusion.

algorithm : {‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’}, optional
Algorithm used to compute the nearest neighbors:
Note: fitting on sparse input will override the setting of this parameter,
using brute force.