This is probably an interview question.Reservoir sampling is used by data scientist to store relevant data in limited storage from large stream of data.
If you have to collect k elements from any array with elements n, such that you probability of each element collected should be same (k/n), you follow two steps,
1) Store first k elements in the storage.
2) When the next element(k+1) comes from the stream obviously you have no space in your collection anymore.Generate a random number from o to n, if the generated random number is less than k suppose l, replace storage[l] with the (k+1) element from stream.
Now, coming back to your question, here storage size is 1.So you will pick the first node,iterate over the list for second element.Now generate the random number ,if its 1, leave the sample alone otherwise switch the storage element from list